1. Field of the Art
The invention relates generally to identifying videos or their parts that are relevant to search terms. In particular, embodiments of the invention are directed to selecting one or more representative thumbnail images based on the audio-visual content of a video.
2. Background
Users of media hosting websites typically browse or search the hosted media content by inputting keywords or search terms to query textual metadata describing the media content. Searchable metadata may include, for example, titles of the media files or descriptive summaries of the media content. Such textual metadata often is not representative of the entire content of the video, particularly when a video is very long and has a variety of scenes. In other words, if a video has a large number of scenes and variety of content, it is likely that some of those scenes are not described in the textual metadata, and as a result, that video would not be returned in response to searching on keywords that would likely describe such scenes. Thus, conventional search engines often fail to return the media content most relevant to the user's search.
A second problem with conventional media hosting websites is that due to the large amount of hosted media content, a search query may return hundreds or even thousands of media files responsive to the user query. Consequently, the user may have difficulties assessing which of the hundreds or thousands of search results are most relevant. In order to assist the user in assessing which search results are most relevant, the website may present each search result together with a thumbnail image. Conventionally, the thumbnail image used to represent a video is a predetermined frame from the video file (e.g., the first frame, center frame, or last frame). However, a thumbnail selected in this manner is often not representative of the actual content of the video, since there is no relationship between the ordinal position of the thumbnail and the content of a video. Furthermore, the thumbnail may not be relevant to the user's search query. Thus, the user may have difficulty assessing which of the hundreds or thousands of search results are most relevant.
Accordingly, improved methods of finding and presenting media search results that will allow a user to easily assess their relevance are needed.